Moderate Bias Research Articles

Comprehensive examination on codon usage bias pattern of the Bovine Ephemeral fever virus

Bovine Ephemeral Fever Virus (BEFV) is a non-contagious virus that commonly infects cattle and water buffalo, reduces milk productivity, decreases the quality of beef, and causes an adverse economic impact on the global livestock industry. However, the evolution of BEFV is unclear, and uncertainty exists regarding its global geodynamics. Consequently, this study aims to comprehend the pattern of viral evolution and gene expression in the BEFV genes G, M, N, and P, including synonymous codons. Additionally, we performed recombination analyses, which exclusively detected recombination signals in the G- and P-genes. Subsequently, a phylogenetic tree was constructed to validate and support these findings. The codon usage bias results showed that the BEFV-selected genes were influenced by both natural and mutation pressure. Furthermore, nucleotide A is more abundant in all the selected genes. The eNC values, ranging from 42.99 to 47.10, revealed the presence of moderate codon usage bias, where gene P exhibited the highest and gene G had the lowest codon usage bias. The neutrality and PR-2 plots, specified codon usage patterns of the genes, are also being shaped by strong selectional pressure. This comprehensive analysis of BEFV genes (G, M, N, and P) sheds light on the molecular evolutionary patterns, co-adaptation, and different genes expression in diverse regions, facilitating the development of preventative programs and insights into viral pathogenesis and vaccine design. Communicated by Ramaswamy H. Sarma

Parametric and nonparametric propensity score estimation in multilevel observational studies.

There has been growing interest in using nonparametric machine learning approaches for propensity score estimation in order to foster robustness against misspecification of the propensity score model. However, the vast majority of studies focused on single-level data settings, and research on nonparametric propensity score estimation in clustered data settings is scarce. In this article, we extend existing research by describing a general algorithm for incorporating random effects into a machine learning model, which we implemented for generalized boosted modeling (GBM). In a simulation study, we investigated the performance of logistic regression, GBM, and Bayesian additive regression trees for inverse probability of treatment weighting (IPW) when the data are clustered, the treatment exposure mechanism is nonlinear, and unmeasured cluster-level confounding is present. For each approach, we compared fixed and random effects propensity score models to single-level models and evaluated their use in both marginal and clustered IPW. We additionally investigated the performance of the standard Super Learner and the balance Super Learner. The results showed that when there was no unmeasured confounding, logistic regression resulted in moderate bias in both marginal and clustered IPW, whereas the nonparametric approaches were unbiased. In presence of cluster-level confounding, fixed and random effects models greatly reduced bias compared to single-level models in marginal IPW, with fixed effects GBM and fixed effects logistic regression performing best. Finally, clustered IPW was overall preferable to marginal IPW and the balance Super Learner outperformed the standard Super Learner, though neither worked as well as their best candidate model.

Can We Reliably Detect Biases that Matter in Observational Studies?

In an observational study of the effects caused by a treatment, biases from unmeasured covariates remain a concern even after successful adjustments for measured covariates. This concern is partly addressed by demonstrating that the qualitative conclusions of the primary analysis would not be altered by small or moderate biases—that these conclusions are insensitive to small or moderate bias. Additionally, the concern is partly addressed by collecting additional information, such as outcomes known to be unaffected by the treatment, and using this information as a test of various biases. Is there a gap between these two activities? Perhaps the study is insensitive to small biases, and we can detect large biases, but the study is sensitive to moderate biases that cannot be detected—that is an informal description of a gap. The concept of “no gap” is defined formally in Definition 3.1, and the probability of “no gap” is determined under various sampling situations. When there is no gap, ask: Are causal conclusions measurably strengthened? If so, by how much? The answer depends upon the covering design sensitivity, Γ⌢, defined to be the smallest bias that can explain both the ostensible effect of the treatment on the primary outcome and the evidence of bias provided by the unaffected outcome. The covering design sensitivity is calculated in various contexts. A small observational study of the effects of light alcohol consumption on HDL cholesterol is used to illustrate ideas and methods.

Exploring the Interpad Gap Region in Ultra-Fast Silicon Detectors: Insights into Isolation Structure and Electric Field Effects on Charge Multiplication.

We present an in-depth investigation of the interpad (IP) gap region in the ultra-fast silicon detector (UFSD) Type 10, utilizing a femtosecond laser beam and the transient current technique (TCT) as probing instruments. The sensor, fabricated in the trench-isolated TI-LGAD RD50 production batch at the FBK Foundry, enables a direct comparison between TI-LGAD and standard UFSD structures. This research aims to elucidate the isolation structure in the IP region and measure the IP distance between pads, comparing it to the nominal value provided by the vendor. Our findings reveal an unexpectedly strong signal induced near p-stops. This effect is amplified with increasing laser power, suggesting significant avalanche multiplication, and is also observed at moderate laser intensity and high HV bias. This investigation contributes valuable insights into the IP region's isolation structure and electric field effects on charge collection, providing critical data for the development of advanced sensor technology for the Compact Muon Selenoid (CMS) experiment and other high-precision applications.

Sex bias in mortality risk changes over the lifespan of bottlenose dolphins.

Research on sex biases in longevity in mammals often assumes that male investment in competition results in a female survival advantage that is constant throughout life. We use 35 years of longitudinal data on 1003 wild bottlenose dolphins (Tursiops aduncus) to examine age-specific mortality, demonstrating a time-varying effect of sex on mortality hazard over the five-decade lifespan of a social mammal. Males are at higher risk of mortality than females during the juvenile period, but the gap between male and female mortality hazard closes in the mid-teens, coincident with the onset of female reproduction. Female mortality hazard is non-significantly higher than male mortality hazard in adulthood, resulting in a moderate male bias in the oldest age class. Bottlenose dolphins have an intensely male-competitive mating system, and juvenile male mortality has been linked to social competition. Contrary to predictions from sexual selection theory, however, male-male competition does not result in sustained male-biased mortality. As female dolphins experience high costs of sexual coercion in addition to long and energetically expensive periods of gestation and lactation, this suggests that substantial female investment in reproduction can elevate female mortality risk and impact sex biases in lifespan.

A Propensity-Score Integrated Approach to Bayesian Dynamic Power Prior Borrowing

Use of historical control data to augment a small internal control arm in a randomized control trial (RCT) can lead to significant improvement of the efficiency of the trial. It introduces the risk of potential bias, since the historical control population is often rather different from the RCT. Power prior approaches have been introduced to discount the historical data to mitigate the impact of the population difference. However, even with a Bayesian dynamic borrowing which can discount the historical data based on the outcome similarity of the two populations, a considerable population difference may still lead to a moderate bias. Hence, a robust adjustment for the population difference using approaches such as the inverse probability weighting or matching, can make the borrowing more efficient and robust. In this article, we propose a novel approach integrating the propensity score for the covariate adjustment and Bayesian dynamic borrowing using power prior. The proposed approach uses Bayesian bootstrap in combination with the empirical Bayes (EB) method using quasi-likelihood for determining the power prior. The performance of our approach is examined by a simulation study. We apply the approach to two Acute Myeloid Leukemia (AML) studies for illustration.

Assessment of WRF (v 4.2.1) dynamically downscaled precipitation on subdaily and daily timescales over CONUS

Abstract. This study analyzes the quality of simulated historical precipitation across the contiguous United States (CONUS) in a 12 km Weather Research and Forecasting model version 4.2.1 (WRF v 4.2.1)-based dynamical downscaling of the fifth-generation ECMWF atmospheric reanalysis (ERA5). This work addresses the following questions. First, how well are the 3 and 24 h precipitation characteristics (diurnal and annual cycles, precipitation frequency, annual and seasonal mean and maximum precipitation, and distribution of seasonal maximum precipitation) represented in the downscaled simulation, compared to ERA5? And second, how does the performance of the simulated WRF precipitation vary across seasons, regions, and timescales? Performance is measured against the National Centers for Environmental Prediction/Environmental Modeling Center (NCEP/EMC) 4 km Stage IV and Oregon State University Parameter-Elevation Regressions on Independent Slopes Model (PRISM) data on 3 and 24 h timescales, respectively. Our analysis suggests that the 12 km WRF exhibits biases typically found in other WRF simulations, including those at convection-permitting scales. In particular, WRF simulates both the timing and magnitude of the summer diurnal precipitation peak as well as ERA5 over most of the CONUS, except for a delayed diurnal peak over the Great Plains. As compared to ERA5, both the month and the magnitude of the precipitation peak annual cycle are remarkably improved in the downscaled WRF simulation. WRF slightly overestimates 3 and 24 h precipitation maximum over the CONUS, in contrast to ERA5, which generally underestimates these quantities mainly over the eastern half of the CONUS. Notably, WRF better captures the probability density distribution (PDF) of 3 and 24 h annual and seasonal maximum precipitation. WRF exhibits seasonally dependent precipitation biases across the CONUS, while ERA5's biases are relatively consistent year round over most of the CONUS. These results suggest that dynamical downscaling to a higher resolution improves upon some precipitation metrics but is susceptible to common regional climate model biases. Consequently, if used as input data for domain-specific models, we suggest moderate bias correction be applied to the dynamically downscaled product.

A Survey Dataset Evaluating Perceptions of Civil Engineering Students about Building Information Modelling (BIM)

The implementation of Building Information Modelling (BIM) technologies has become increasingly central in the design, construction and maintenance of both civil structures and infrastructures. As more and more software houses develop new BIM software solutions and a wide range of private and public stakeholders employ them, several educational institutes across the globe strive to expand their teaching portfolio to encompass learning and teaching of BIM. This dataset deals with the perceptions expressed by all the civil engineering undergraduate students who attended an academic course specifically about BIM at University of Stavanger (UiS), Norway, during the second semester 2022. The survey was divided into five parts and collected information regarding as many overarching aspects: socio-demographic data, perceptions about BIM before and after course attendance, satisfaction about the academic course and the way it was conducted. Considering the very moderate sample size (28 students) and potential biases due to the specific context of the University of Stavanger, the dataset can provide a useful insight into teaching approaches and future curriculum development, rather than indicating major and generalized trends in BIM education. As the questionnaire responses shed light on the feedbacks and perceptions expressed by university students dealing with BIM for their first time, the formed dataset can offer a straightforward appreciation of students’ cognitive behaviour in BIM education.

Improving the crystallinity and texture of oblique-angle-deposited AlN thin films using reactive synchronized HiPIMS

Many technologies, such as surface-acoustic-wave (SAW) resonators, sensors, and piezoelectric MEMS require highly-oriented and textured functional thin films. The best results are typically achieved for on-axis sputter geometries, but in some scenarios, this is not feasible, such as during co-deposition from multiple magnetrons or when coating substrates with high aspect ratios. Ionized physical vapor deposition (PVD) techniques such as HiPIMS can be used to accelerate the film-forming species onto the growing film using substrate-bias potentials, thus increasing adatom mobility and film texture. However, gas-ion incorporation can limit the feasibility of such synthesis approaches for defect-sensitive functional thin films. This work reports on the oblique-angle deposition of highly textured, c-axis oriented AlN (0002) films using reactive metal-ion synchronized HiPIMS. AlN thin films deposited using direct current magnetron sputtering (DCMS) and HiPIMS are discussed for comparison and the effect of ion irradiation through substrate biasing is investigated. We find that combining HiPIMS with a moderate substrate bias of only −30 V improves the crystalline quality and texture of the films significantly, while the process-gas incorporation and point defects formation can be further reduced by synchronizing the negative substrate bias potential to the Al-rich fraction of each HiPIMS pulse. In addition to a pronounced out-of-plane texture, the films show uniform polarization of the grains making this synthesis route suitable for piezoelectric applications. While the compressive stress in the films is still comparatively high, the results already demonstrate, that metal-ion synchronized HiPIMS can yield promising results for the synthesis of functional thin films under oblique-angle deposition conditions - even with low substrate-bias potentials.

Widespread partisan gerrymandering mostly cancels nationally, but reduces electoral competition

Congressional district lines in many US states are drawn by partisan actors, raising concerns about gerrymandering. To separate the partisan effects of redistricting from the effects of other factors including geography and redistricting rules, we compare possible party compositions of the US House under the enacted plan to those under a set of alternative simulated plans that serve as a nonpartisan baseline. We find that partisan gerrymandering is widespread in the 2020 redistricting cycle, but most of the electoral bias it creates cancels at the national level, giving Republicans two additional seats on average. Geography and redistricting rules separately contribute a moderate pro-Republican bias. Finally, we find that partisan gerrymandering reduces electoral competition and makes the partisan composition of the US House less responsive to shifts in the national vote.

Systematic review of preoperative n-3 fatty acids in major gastrointestinal surgery

ObjectivesPerioperative nutrition aims to replenish nutritional stores before surgery and reduce postoperative complications. ‘Immunonutrition’ (including omega-3 fatty acids) may modulate the immune system and attenuate the postoperative inflammatory response. Hitherto,...

Investigation of the structural and temperature-dependent electrical properties of MZnO (M = Ce and Sm) Schottky diode devices fabricated using the sol–gel spin-coating technique

In the present study, the Schottky diode devices based on Ce and Sm co-doped ZnO thin films were fabricated using the sol–gel spin-coating technique with Pd and Pt as Schottky contacts. The structural and electrical properties of the fabricated Schottky diode devices were investigated at room temperature and in the temperature range of 320–160 K. The crystalline structure of the prepared films was studied using X-ray diffraction spectroscopy. The I–V characteristics of the fabricated Schottky diode devices based on Pd and Pt Schottky contacts manifest good diode behavior with the rectification of nine and ten orders of magnitudes, respectively. The ideality factor for Pd-based Schottky diode was found to decrease with temperature, and the lowest value obtained at 160 K was 1.3, while for the Pt-based Schottky diode, the ideality factor was found to increase with decreasing temperature. Moreover, by using two Gaussian models, the barrier height for Pt Schottky diodes was found to decrease with decreasing temperature indicating the inhomogeneity in the barrier height. Furthermore, alongside the thermionic emission theory, the fabricated Schottky diode parameters were also analyzed with Cheung–Cheung and the modified Nord methods. Finally, the current transport mechanism in both fabricated Pd and Pt was found to be controlled by an Ohmic, trap-filled voltage and space-charge-limited current mechanisms in the low, moderate and higher voltage bias, respectively.

Patterns of attentional biases in children and emotional symptoms during the COVID-19 pandemic: a two-wave longitudinal study

BackgroundIt is unknown how the patterns of negative and positive attentional biases in children predict fear of COVID-19, anxiety symptoms, and depression symptoms during the COVID-19 pandemic. The study identified profiles of negative and positive attentional biases in children and examined their association with emotional symptoms during the COVID-19 pandemic.Method264 children (girls: 53.8% and boys: 46.2%) of 9–10 years born in Hong Kong or mainland China from a primary school in Shenzhen, People’s Republic of China were involved in a two-wave longitudinal study. Children completed the COVID-19 Fear Scale, the Revised Child Anxiety and Depression Scale, and the Attention to Positive and Negative Information Scale to measure fear of COVID-19, anxiety and depression symptoms, and negative and positive attentional biases in classrooms. After six months, they completed the second assessment of fear of COVID-19, anxiety symptoms, and depression symptoms in classrooms. Latent profile analysis was conducted to reveal distinct profiles of attentional biases in children. A series of repeated MANOVA was performed to examine the association of profiles of attentional biases to fear of COVID-19, anxiety symptoms, and depression symptoms across 6 months.ResultsThree profiles of negative and positive attentional biases were revealed in children. Children with a “moderate positive and high negative attentional biases” profile had significantly higher fear of the COVID-19 pandemic, anxiety symptoms, and depression symptoms than children with a “high positive and moderate negative attentional biases” profile. Children with a “low positive and negative attentional biases” profile were not significantly different in fear of COVID-19, anxiety symptoms, and depression symptoms than those with the other two profiles.ConclusionsPatterns of negative and positive attentional biases were related to emotional symptoms during the COVID-19 pandemic. It might be important to consider children's overall patterns of negative and positive attentional biases to identify children at risk of higher emotional symptoms.

Tuning the microstructure and hydrogen permeability of VC/V composite membranes by radio frequency magnetron sputtering with applied substrate bias

Our recent work has shown that vanadium carbide (VC) films prepared by radio frequency magnetron sputtering (RFMS) can be used as H2 dissociation/recombination catalysts on vanadium (V) for high temperature hydrogen separation. During the deposition of VC on V by RFMS, substrate bias was further applied to tune the microstructure and hydrogen permeability of the VC/V composite membranes. It is found that moderate substrate bias during RFMS generates nanocrystalline VC films with hexagonal close packed V2C (hcp-V2C) phase, which exhibits finer grain size and higher carbon vacancy density compared to the films with face centered cubic VC (fcc-VC) phase prepared by RFMS without bias. The increase in carbon vacancy density results in an increase in the electron density around the Fermi level (EF) and a lowering of the d-band center for the VC, which contributes to its catalytic activity. The resulted VC/V composite membranes show significantly enhanced hydrogen permeability, particularly at all temperatures evaluated, above that of industrially used Pd. This work demonstrates that RFMS with applied substrate bias as microstructural engineering is an efficient method to prepare highly hydrogen-permeable VC/V composite membranes.

Effects of social support, anxiety, and hope levels on cognitive bias in patients with nasogastric/nasoenteric tubes

Unplanned extubation is a common adverse event and an important indicator of quality and safety of care. It is well recognized that the incidence of unplanned extubation of nasogastric/nasoenteric tubes is higher than that of other devices. Theory and previous research have suggested that cognitive bias in conscious patients with nasogastric/nasoenteric tubes may lead to unplanned extubation, and that social support, anxiety, and hope are influencing factors of cognitive bias. Therefore, the objective of this study was to investigate the effects of social support, anxiety, and hope levels on cognitive bias in patients with nasogastric/nasoenteric tubes. In this cross-sectional study, 438 patients with nasogastric/nasoenteric tubes were selected from 16 hospitals in Suzhou from December 2019 to March 2022 by convenience sampling method. The participants were assessed using the General Information Questionnaire, Perceived Social Support Scale, Generalized Anxiety Disorder-7, Herth Hope Index, and Cognitive Bias Questionnaire for patients with nasogastric/nasoenteric tubes. The structural equation model was established with AMOS 22.0 software. The cognitive bias score of patients with nasogastric/nasoenteric tubes was 2.82±0.61. Patients' perceived levels of social support and hope were negatively correlated with their cognitive bias (r=-0.395 and -0.427, respectively, P<0.05), and anxiety was positively correlated with cognitive bias (r=0.446, P<0.05). Structural equation model analysis showed that anxiety had a direct positive effect on cognitive bias, with an effect value of 0.35 (P<0.001), and hope level had a direct negative effect on cognitive bias with an effect value of -0.33 (P<0.001). Social support had a direct negative effect on cognitive bias and was also shown to indirectly affect cognitive bias through anxiety and hope levels. The effect values were -0.22, -0.12, and -0.19 (P<0.001), for social support, anxiety, and hope, respectively. Social support, anxiety, and hope explained 46.2% of the total variation in cognitive bias. Moderate cognitive bias is noted in patients with nasogastric/nasoenteric tubes, and social support significantly affects cognitive bias. Anxiety and hope level play a mediating role in social support and cognitive bias. Positive psychological intervention and the obtention of positive support could improve the cognitive bias of patients with nasogastric/nasoenteric tubes.

Implicit bias toward people with disability: A systematic review and meta-analysis.

People with disabilities (PWD) experience barriers to accessibility and employment, harming their quality of life. Strategies aimed at reducing disparity for PWD have not changed key statistics such as unemployment rates. Previous research has focused on explicit attitudes, generally found to be positive, prompting investigation into factors such as implicit bias. This systematic review and meta-analysis investigated implicit bias toward PWD and associated factors. Forty-six peer-reviewed studies published between January 2000 and April 2020 utilizing the Implicit Association Test were included. Of these, 12 studies met the inclusion criteria for meta-analysis. A significant moderate pooled effect (mean difference = 0.503, 95% CI [0.497-0.509], p < .001) was found, suggesting moderate negative implicit attitudes toward general disability. Negative implicit attitudes were also found toward physical, and intellectual disability. PWD were implicitly stereotyped as incompetent, cold, and "child-like." Findings were inconsistent for factors associated with bias including age, race, sex, and individual differences. Contact with PWD may be associated with implicit bias; however, measures were inconsistent. This review has found moderate negative implicit biases toward PWD, however, factors associated with this bias remain unclear. Further research should investigate implicit bias toward specific disability groups and strategies to shift such biases. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The Influence of Financial Literacy as a Mediation of the Relationship Between Behavioral Bias and Decisions in Investing Employees in Jabodetabek

This study aims to determine how Behavior Biases influences people in making investment decisions. The Independent Variable used in this study is Behavior Biases consist of Overconfidence, Herding, Risk-aversion and Disposition. Dependent Variable used in this study is Investment Decision. The moderating variable used in this study is Financial Literacy. This study taking samples from workers lives in Jabodetabek (Jakarta, Bogor, Depok and Bekasi), Indonesia. By using data collection method via Google Forms spreaded to public of Jabodetabek 2022-2023 thus obtaining 353 respondents who became the research sample. The data analysis used to test the hypothesis is the analysis of the regression equation using SEM PLS (Structural Equation Model Partial Least Square) program. The result of this study indicates that Bias Behavior (Overconfidence, Herding, Risk Aversion, Disposition) has an influence on Investment Decisions, while Financial Literacy has no effect and Financial Literacy doesn't moderate Bias Behavior towards Investment Decisions. This finding has implications for potential investors to consider learning Financial Literacy more in their investment decisions.

Exploring Gender Bias in Six Key Domains of Academic Science: An Adversarial Collaboration.

We synthesized the vast, contradictory scholarly literature on gender bias in academic science from 2000 to 2020. In the most prestigious journals and media outlets, which influence many people's opinions about sexism, bias is frequently portrayed as an omnipresent factor limiting women's progress in the tenure-track academy. Claims and counterclaims regarding the presence or absence of sexism span a range of evaluation contexts. Our approach relied on a combination of meta-analysis and analytic dissection. We evaluated the empirical evidence for gender bias in six key contexts in the tenure-track academy: (a) tenure-track hiring, (b) grant funding, (c) teaching ratings, (d) journal acceptances, (e) salaries, and (f) recommendation letters. We also explored the gender gap in a seventh area, journal productivity, because it can moderate bias in other contexts. We focused on these specific domains, in which sexism has most often been alleged to be pervasive, because they represent important types of evaluation, and the extensive research corpus within these domains provides sufficient quantitative data for comprehensive analysis. Contrary to the omnipresent claims of sexism in these domains appearing in top journals and the media, our findings show that tenure-track women are at parity with tenure-track men in three domains (grant funding, journal acceptances, and recommendation letters) and are advantaged over men in a fourth domain (hiring). For teaching ratings and salaries, we found evidence of bias against women; although gender gaps in salary were much smaller than often claimed, they were nevertheless concerning. Even in the four domains in which we failed to find evidence of sexism disadvantaging women, we nevertheless acknowledge that broad societal structural factors may still impede women's advancement in academic science. Given the substantial resources directed toward reducing gender bias in academic science, it is imperative to develop a clear understanding of when and where such efforts are justified and of how resources can best be directed to mitigate sexism when and where it exists.

What can we learn about selective attention processes in individuals with chronic pain using reaction time tasks? A systematic review and meta-analysis.

Information-processing biases such as attentional, interpretation, and memory biases are believed to play a role in exacerbating and maintaining chronic pain (CP). Evidence suggests that individuals with CP show attentional bias toward pain-related information. However, the selective attentional processes that underpin this bias are not always well outlined in the literature. To improve current understanding, a systematic review was performed using a descriptive synthesis of reaction time-based studies. A random-effects meta-analysis was added to explore whether the results of previous meta-analyses would be confirmed using studies with a larger sample size. For this review, 2008 studies were screened from 4 databases, of which 34 (participant n = 3154) were included in the review and a subset of 15 (participant n = 1339) were included in the meta-analysis. Review results were summarised by producing a descriptive synthesis for all studies. Meta-analysis results indicated a mild significant attentional bias toward sensory pain-related information (k = 15, g = 0.28, 95% CI [0.16, 0.39], I 2 = 43.2%, P = 0.038), and preliminary evidence of significant moderate bias towards affective pain-related information (k = 3, g = 0.48, 95% CI [0.23, 0.72], I 2 = 7.1%, P = 0.341) for CP groups compared with control groups. We explored the main tasks, stimuli, and CP subtypes used to address attentional biases and related processes. However, variation across studies did not allow for a decisive conclusion about the role of stimulus, task type, or related attentional processes. In addition, a table of CP attention-related models was produced and tested for reliability. Finally, other results and recommendations are discussed.

Impact of Synoptic Wind Intensification and Relaxation on the Dynamics and Heat Budget of the South Senegalese Upwelling Sector

Abstract In addition to their well-known seasonal cycle, eastern boundary upwelling systems (EBUS) undergo modulation on shorter synoptic to intraseasonal time scales. Energetic intensifications and relaxations of upwelling-favorable winds with 5–10-day typical time scales can impact the EBUS dynamics and biogeochemical functioning. In this work the dynamical effects of wind-forced synoptic fluctuations on the South Senegalese Upwelling Sector (SSUS) are characterized. The region geomorphology is unique with its wide continental shelf and a major coastline discontinuity at its northern edge. The ocean response to synoptic events is explored using a modeling framework that involves applying idealized synoptic wind intensification or relaxation to a five-member climatological SSUS ensemble run. Model evaluation against sparse midshelf in situ observations indicates qualitative agreement in terms of synoptic variability of temperature, stratification, and ocean currents, despite a moderate but systematic bias in current intensity. Modeled synoptic wind and heat flux fluctuations produce clear modulations of all dynamical variables with robust SSUS-scale and mesoscale spatial patterns. A mixed layer heat budget analysis is performed over the continental shelf to uncover the dominant processes involved in SSUS synoptic variability. Modulations of horizontal advection and atmospheric forcing are the leading-order drivers of heat changes during either wind intensification or relaxation while vertical dynamics is of primary importance only in a very localized area. Also, modest asymmetries in the oceanic responses to upwelling intensification and relaxation are only identified for meridional velocities. This brings partial support to the hypothesis that synoptic variability has a modest net effect on the climatological state and functioning of upwelling systems dynamics.